High Heritability Research Articles

Studies on genetic variability parameters for seed yield and its component traits in mungbean [Vigna radiata (L.) Wilczek] germplasm under arid environment

Genetic variability is the most important factor for the success of any crop improvement program. Hence, the evaluation of germplasm has to be conducted as a preliminary step to study the extent of variability available in the germplasm and to identify suitable high-yielding genotypes that can be utilized in the crop improvement program. The present investigation was carried out to estimate genetic variability, heritability, and genetic advance for yield and yield contributing characters among seventy-nine diverse genotypes of mungbean for eleven quantitative traits. Significant differences were observed among genotypes for all eleven characters studied. The high degree of genetic variability along with high heritability and high genetic advance as percent of mean were recorded for seed yield per plant, number of pods per plant, harvest index, biological yield per plant, and plant height; which indicates that these characteristics were under the control of additive gene action and therefore, form the basis of selection for the mungbean improvement program.

Deep Trans-Omic Network Fusion for Molecular Mechanism of Alzheimer's Disease.

There are various molecular hypotheses regarding Alzheimer's disease (AD) like amyloid deposition, tau propagation, neuroinflammation, and synaptic dysfunction. However, detailed molecular mechanism underlying AD remains elusive. In addition, genetic contribution of these molecular hypothesis is not yet established despite the high heritability of AD. The study aims to enable the discovery of functionally connected multi-omic features through novel integration of multi-omic data and prior functional interactions. We propose a new deep learning model MoFNet with improved interpretability to investigate the AD molecular mechanism and its upstream genetic contributors. MoFNet integrates multi-omic data with prior functional interactions between SNPs, genes, and proteins, and for the first time models the dynamic information flow from DNA to RNA and proteins. When evaluated using the ROS/MAP cohort, MoFNet outperformed other competing methods in prediction performance. It identified SNPs, genes, and proteins with significantly more prior functional interactions, resulting in three multi-omic subnetworks. SNP-gene pairs identified by MoFNet were mostly eQTLs specific to frontal cortex tissue where gene/protein data was collected. These molecular subnetworks are enriched in innate immune system, clearance of misfolded proteins, and neurotransmitter release respectively. We validated most findings in an independent dataset. One multi-omic subnetwork consists exclusively of core members of SNARE complex, a key mediator of synaptic vesicle fusion and neurotransmitter transportation. Our results suggest that MoFNet is effective in improving classification accuracy and in identifying multi-omic markers for AD with improved interpretability. Multi-omic subnetworks identified by MoFNet provided insights of AD molecular mechanism with improved details.

Field response and genetic variability of elite spring bread wheat (Triticum aestivum L.) genotypes for septoria tritici blotch under natural infection in Northwest Ethiopia

AbstractFungal diseases cause significant yield loss to wheat production. Septoria tritici blotch (STB), caused by the ascomycete fungus Zymoseptoria trtici, is one of the major fungal diseases affecting wheat production worldwide. In Ethiopia, STB is a severe problem that causes significant yield loss in high and mid‐altitude wheat‐growing areas. The use of resistant varieties is one of the sustainable disease management strategies, particularly for resource‐poor farmers in developing countries. Two hundred and fifty bread wheat genotypes were evaluated to identify septoria tritici resistant genotypes and estimate the extent of genetic variability for resistance to STB and other economically important traits using alpha lattice design under natural infestation in two STB hotspot environments. Analysis of variance revealed highly significant differences among genotypes, environment, and genotype × environment interaction for all traits measured. The genetic coefficient of variance was lower than the phenotypic coefficient of variance for all traits studied, and both test environments showed the influence of the environment on trait expression. High and moderate heritability values were observed for the septoria disease severity parameters, indicating that the STB resistance trait was less influenced by the environment. The days to heading and plant height were inversely correlated with disease severity. This suggests that genotypes with tall plant height and long maturity period could be resistant to septoria tritici blotch through escape mechanisms. Four of the genotypes, namely, G‐215, G‐255, G‐257, and G‐258, were found to be resistant across all locations. These and other promising genotypes will be used in future breeding programmes to select or develop high‐yielding and STB‐resistant bread wheat genotypes that can be deployed in septoria tritici blotch‐prone areas. Highly susceptible genotypes will also be used as controls for STB resistance breeding programmes.

Assessing selection potential for Pacific oyster (Crassostrea gigas) to a North American OsHV-1 μvar: Comparing two experimental assay methods

Ostreid Herpesvirus - 1 is a global threat to Pacific oyster aquaculture as catastrophic farm losses have occurred where OsHV-1 microvariants (μvars) become endemic. Genetic selection has proven effective for increasing survival to OsHV-1 exposure in multiple Pacific oyster breeding programs, but a novel μvar detected in San Diego Bay California has the potential to severely impact commercial aquaculture along the North American Pacific coast as no OsHV-1 μvar selected population is available commercially. Using a Molluscan Broodstock Program population descending from imports originating in the Miyagi prefecture (Japan), we evaluated the potential for genetic selection to improve survival against the San Diego Bay OsHV-1 μvar using a laboratory trial. Two experimental methods were evaluated, a common garden method where all 15 full-sibling families were pooled, and a petri dish method, where each family was confounded within replicate. No striking differences were found between experimental methods, and both experiments displayed high heritability (0.69 and 0.64) of the tested trait, a broad range of estimated breeding values, and a moderate prediction accuracy for the survival trait. A significant genotype-by-environment interaction occurred, highlighting variability in laboratory-based disease challenges, but the two experiments yielded similar results with minor to moderate re-ranking of mean family survival. Overall, the Miyagi population of Pacific oysters curated by the Molluscan Broodstock Program is a promising population to use for artificial selection to increase survival against San Diego Bay OsHV-1 μvar in attempts to obviate farm losses if the virus expands its currently isolated range.

Studies on Genetic Variability, Correlation and Path Coefficient Analysis for Yield and Yield Contributing Traits in Bread Wheat (Triticum aestivum L.)

A study was undertaken to analyse the genetic variability, correlation and estimates path coefficient analysis of yield and yield contributing traits in twenty-eight wheat genotypes grown at BAU Agricultural Farm, ranchi during Rabi season of 2019-2020 in three different dates of sowing with an interval of 15 days which is considered as three environments E1, E2, E3. In this investigation the pooled analysis of variance revealed that the treatments were highly significant for all the characters. Wide genetic variation was observed among genotypes for plant height, number of grains per spike, 1000 kernel weight, days to maturity and flag leaf area. Considering genetic parameters, high genotypic co-efficient of variation (GCV), was observed for 1000 kernel weight (11.95), no of grains per spike (12.73), flag leaf area (13.74), spike length (15.83), grain yield per plant (17.64), no of effective tillers (18.38) Whereas, low GCV was observed for plant height (3.49), days to 50% flowering (1.46), days to maturity (2.54) and harvest index (6.90). In most of the cases, phenotypic variances were higher than the genotypic variances. Environmental variance is much higher in harvest index (35.64), days to 50% flowering (33.47). low environmental variance was observed in plant height (16.75), flag leaf area (10.29), days to maturity (13.93), no of grains per spike (14.07), spike length (0.49) and biological yield (35.64). High heritability with low genetic advance in per cent of mean was observed for plant height, days to maturity, days to 50% flowering & harvest index which indicated the involvement of non-additive gene action for the expression of this character and selection for such trait might not be rewarding. High heritability with high genetic advance in per cent of mean was observed for grain yield per plant (27.73), no of grains per spike (20.93), 1000 kernel weight (23.58) and no of effective tillers (27.91) indicating that these traits were under additive gene control and selection for genetic improvement for these traits would be effective. Biological yield had high positive and significant correlation with plant height, number of effective tillers and number of grains per spike. Path coefficient analysis revealed maximum direct contribution towards yield per plot with sheath length followed by grains per spike.

Mean Performance and Genetic Variability Exploration for Fruit Yield and its Attributing Traits in Tomato (Solanum lycopersicum L.)

The present study was conducted to access the relative performance, genetic variability, genetic advance and heritability in thirty genotypes of tomato crop. The crop was sown under Randomized Block Design (RBD) in three replications at Regional Research Station Karnal, CCS Haryana Agricultural University, during the Autumn Winter season of 2021-22. The observations were recorded for eight parameters pertaining to the fruit yield and its attributing traits in tomato. Statistics from analysis of variance showed substantial differences among the genotypes that unveils the plausible presence of significant genetic variability which could be positively exploited in crop improvement programs. The results obtained in the experiment showed that Pusa Ruby (38 days) was earliest to flower in 50% plants followed by EC-631351 (40 days). Genotype Selection 7 took the least (66) number of days to first picking and genotype Kashi Hemant took the maximum (155 days) number of days to last picking. Genotype EC-615056 recorded the maximum (57.71 g) average fruit weight and genotypes namely EC-631457, EC-631357 and Pusa Early Dwarf observed highest fruit yield per plant. Narrow differences were recorded for the phenotypic and genotypic coefficients of variation for all the characters, which denotes that environment had very little influence in expression of the characters and phenotype truly represents the genotype. High to moderate magnitude of genotypic coefficient of variation and phenotypic coefficient of variation was recorded for almost all the characters in our investigation. Plant characters days to first picking, days to 50% flowering, days to last picking, plant height at harvest recorded high (>70%) magnitude of heritability in broad sense implying least influence of environment over these characters. High heritability coupled with high genetic advance was observed for characters like days to 50% flowering and plant height at harvesting.

Exome sequencing implicates ancestry-related Mendelian variation at SYNE1 in childhood-onset essential hypertension.

Childhood-onset essential hypertension (COEH) is an uncommon form of hypertension that manifests in childhood or adolescence and, in the United States, disproportionately affects children of African ancestry. The etiology of COEH is unknown, but its childhood onset, low prevalence, high heritability, and skewed ancestral demography suggest the potential to identify rare genetic variation segregating in a Mendelian manner among affected individuals and thereby implicate genes important to disease pathogenesis. However, no COEH genes have been reported to date. Here, we identify recessive segregation of rare and putatively damaging missense variation in the spectrin domain of spectrin repeat containing nuclear envelope protein 1 (SYNE1), a cardiovascular candidate gene, in 3 of 16 families with early-onset COEH without an antecedent family history. By leveraging exome sequence data from an additional 48 COEH families, 1,700 in-house trios, and publicly available data sets, we demonstrate that compound heterozygous SYNE1 variation in these COEH individuals occurred more often than expected by chance and that this class of biallelic rare variation was significantly enriched among individuals of African genetic ancestry. Using in vitro shRNA knockdown of SYNE1, we show that reduced SYNE1 expression resulted in a substantial decrease in the elasticity of smooth muscle vascular cells that could be rescued by pharmacological inhibition of the downstream RhoA/Rho-associated protein kinase pathway. These results provide insights into the molecular genetics and underlying pathophysiology of COEH and suggest a role for precision therapeutics in the future.

Genetic Architecture, Studies to Identify the Selection Criteria for Yield in Long Duration Rice Lines (Oryza sativa L.)

Genetic Architecture, Studies to Identify the Selection Criteria for Yield in Long Duration Rice Lines (Oryza sativa L.)

225 Genomic diversity of Katahdin sheep and impacts on genomic prediction

Abstract In the late 1950s, Katahdin hair sheep were developed as a composite breed of medium size and moderate prolificacy, with potential to express resistance to gastrointestinal nematodes. With its increasing popularity and the recent adoption of genomic prediction in the Katahdin breeding program, evaluating the genetic diversity in this breed is necessary. Prediction accuracies rely on the strength of genetic relationships. That strength often increases with selection using genomically-enhanced estimated breeding values; however, it carries the risk of decreasing diversity. We aim to characterize the genetic diversity present in the breed and the subsequent impact on the accuracies of genomic predictions. Genotypes on Katahdin sheep from member flocks in the National Sheep Improvement Program were used. Data from two medium density 50k bead chips and one high density 600k bead chip were merged and limited to shared autosomal single nucleotide polymorphisms (SNP). After quality control, there were 9,705 animals and 31,984 SNP remaining. Only for analyses of inbreeding and heterozygosity, linkage disequilibrium (LD) pruning was performed; variants with an LD score exceeding 0.8 were removed with 29,904 SNP remaining. To determine the extent of population structure, principal component (PC) analysis was conducted with PC one and PC two explaining 4.9% and 3.8% of the variation in the population, respectively. When examining subpopulations, a single ancestral population explained 99.9% of the genetic variation among animals. When clustered by identity-by-state, all animals were placed in a single cluster. Inbreeding coefficients were estimated with four methods: method of moments, variance-standardized relationship minus one, excess homozygosity, and correlation between uniting gametes. Across methods, average inbreeding coefficients ranged from 1.14% to 1.20% with Pearson and Spearman correlations ranging from -0.51 to 0.91 (Table 1). Historical effective population sizes (Ne) were estimated for earlier generations, and a linear regression fit to predict more recent Ne. At the founding of the breed, historical Ne was estimated to be 310, and the current Ne was estimated to be 150. Effects of Ne on the accuracy of genomic predictions were examined for reference population sizes ranging from 1k to 25k for traits of low (0.1), moderate (0.3), and high (0.5) heritabilities. The corresponding number of effective chromosomal segments were 2NeL, where L was the length of the genome in morgans (26M). Accuracies of genomic predictions increased as the reference population size grew, with only marginal gains once the population exceeded 15k. Overall, there were no detectable genetic subpopulations in the Katahdin breed. Current levels of inbreeding were low. With a small Ne the breed can achieve high accuracy for genomic predictions by aiming for a reference population of 15k animals. Negative impacts on genetic diversity due to genomic selection are not of immediate concern.

Genetic parameters for resistance to field mortality outbreaks and resistance to a pathogenic strain of Vibrio splendidus in Mytilus edulis, Mytilus galloprovincialis and natural hybrid

Since 2014, abnormal mussel mortality (AMM) outbreaks have occurred along the French Atlantic coasts and mortality rates differed among years and sites (30–100%). Still, the etiology of the AMM is undefined. Our study explores the resistance of two mussel species (Mytilus edulis and Mytilus galloprovincialis) and natural hybrids (NH) cultivated in France to AMM. One hundred mussel families were produced using six wild mussel populations in January/February 2017. Mussels were tested in two sites, La Floride (LF) and Maison Blanche (MB), in October 2017, and their mortality/growth was recorded until June 2018. AMM was observed at MB during spring 2018, and reached 70%, 43%, and 63%, for M. edulis, M. galloprovincialis, and NH, respectively, at endpoint. In contrast, mortality was low in LF, reaching 11%, 30%, and 22%, respectively. Heritability for mortality was low to moderate in both sites ranging from 0.12 to 0.37 with higher values in M. edulis, intermediate for NH, and the lowest for M. galloprovincialis. A significant genotype-by-environment interaction was found for mortality between sites, with low genetic correlations not significantantly different from zero (−0.05 to 0.43). In July 2018, mussel families were evaluated under experimental infection using a pathogenic strain of Vibrio splendidus isolated during AMM in 2014. The mean mortality after 72 h post-injection was 53%, 22%, and 31% for M. edulis, M. galloprovincialis, and NH, respectively. The lowest heritability estimates were obtained for NH (0.21) and the highest for M. galloprovincialis (0.41), and the genetic correlation between AMM in MB and experimental infection was not significantly different from 0, suggesting that this Vibrio strain, is not the major cause of AMM outbreak observed in MB in 2018. Finally, significant genetic variation was observed for growth traits with mostly high heritability (> 0.44) for both species. Interestingly, genetic correlation between mortality and growth was weak and non-significant from zero.

Assessment of Genetic Variability for Nutrient Status in Grain and Leaves of Amaranthus Genotypes

In the present investigation 18 different genotypes of amaranthus were analyzed for nutrient status and noticeable range of major nutrients were reported in leaves and grains. The phenotypic coefficient of variation and genotypic coefficient of variation was maximum for leaf color constituent b* i.e., 63.76 and 63.76 while, minimum in case of leaf moisture i.e., 6.62 and 3.03, respectively. High heritability was observed for all the traits, maximum was recorded for leaf color constituent b* (100%) and minimum was observed for leaf moisture (70.09%). High heritability (h2 = 99.19%) with high genetic advance (GA=73.90%) as percentage of mean was observed for leaf vitamin C, which indicated that additive gene effects were more important for that trait. High genetic advance as per cent of mean was observed for leaf color constituent b* (131.34) however, lowest for days to leaf moisture (5.23) which indicates the preponderance of additive genes and selection will be effective for improvement of these traits having high heritability with genetic advance as percent of mean.

Genetically correlated leaf tensile and morphological traits are driven by growing season length in a widespread perennial grass.

Leaf tensile resistance, a leaf's ability to withstand pulling forces, is an important determinant of plant ecological strategies. One potential driver of leaf tensile resistance is growing season length. When growing seasons are long, strong leaves, which often require more time and resources to construct than weak leaves, may be more advantageous than when growing seasons are short. Growing season length and other ecological conditions may also impact the morphological traits that underlie leaf tensile resistance. To understand variation in leaf tensile resistance, we measured size-dependent leaf strength and size-independent leaf toughness in diverse genotypes of the widespread perennial grass Panicum virgatum (switchgrass) in a common garden. We then used quantitative genetic approaches to estimate the heritability of leaf tensile resistance and whether there were genetic correlations between leaf tensile resistance and other morphological traits. Leaf tensile resistance was positively associated with aboveground biomass (a proxy for fitness). Moreover, both measures of leaf tensile resistance exhibited high heritability and were positively genetically correlated with leaf lamina thickness and leaf mass per area (LMA). Leaf tensile resistance also increased with the growing season length in the habitat of origin, and this effect was mediated by both LMA and leaf thickness. Differences in growing season length may promote selection for different leaf lifespans and may explain existing variation in leaf tensile resistance in P. virgatum. In addition, the high heritability of leaf tensile resistance suggests that P. virgatum will be able to respond to climate change as growing seasons lengthen.

Effect of genetic and sex effect on genomic prediction for horn development in Nellore cattle

This study aimed to evaluate the influence of phenotypic classification of horn development, animal sex effect, and non-autosomal SNP (single nucleotide polymorphism) markers on the genetic parameters and genomic prediction ability for horn development in Nellore cattle using the single-step genomic best linear unbiased prediction method. The polled phenotype was evaluated in two (presence and absence of horns), three (scurs and polled offspring from a horned parent, and the polled and horned animals), and four (absence of horn, polled born to a parent with horn, scurs, and presence of horn) phenotypic categories. A total of 12 statistical models were evaluated. The variance components were estimated using the THRGIBBS1F90 software, and a threshold animal model was used for genomic prediction analyses with the single-step genomic BLUP (ssGBLUP) procedure. Accuracy, bias, and dispersion parameters were evaluated based on the linear regression (LR) method. The highest heritability (0.84) was obtained when the polled character was evaluated as a binary trait. The lowest heritability estimates (0.44 to 0.45) for horn development were obtained when the phenotype was classified into three categories. For the same horn development classification method, the heritability estimates were similar regardless of the genomic evaluated models and fixed effects included in the model. For models considering four and three phenotypic categories for horn development, the inclusion of the sex effect as a fixed effect within the CG did not improve the accuracy, bias, and dispersion of genomic predictions for horn development. Analyzing the trait with binary expression, the highest prediction accuracy was observed when the effect of sex was not included in the CG and without the SNPs in the sex chromosomes. These models displayed the highest dispersion, pointing out the low robustness of genomic prediction. In addition, models that use less than four categories to classify the horn development phenotype, with no discrimination between polled and homozygous polled displayed lower prediction ability. The inclusion of non-autosomal SNPs in the analyses for the models considering four phenotypic categories leads to an improvement in prediction accuracy in 5,26 %, bias, and dispersion reduction, 37 % and 4,55 %, respectively, compared with models that only considered autosomal SNPs. The selection using genomic information for the polled trait is feasible, and it is an alternative to obtaining polled Nellore animals. The binary coding of horn development is an unsuitable oversimplification of polled phenotype, and probably, the genetic background of horn development is more complex than previously proposed. The most adequate prediction model to evaluate the horn development in Nellore cattle was considering four phenotypic categories and including non-autosomal SNP in the analyses for genomic prediction purposes of naturally genetically polled animals. Genetic dehorning can be adopted on a large scale as a low-cost and non-invasive approach to increase the frequency of hornless animals using genomic information and mating strategies.

Assessment of Variability, Heritability and Genetic Advance in Groundnut (Arachis hypogaea L.)

The present research, entitled “Assessment of Variability, Heritability, and Genetic Advance in Groundnut (Arachis hypogaea L.),” was conducted on 15 genotypes with 16 characteristics. The analysis of variance revealed that genotypic variation was extremely significant for all of the traits under consideration. Additionally, the phenotypic coefficient of variance was larger than the genotypic coefficient of variation in magnitude. Quantitative features include the number of pods and kernels per plant, days to bloom initiation, days to 50% flowering, and days to maturity, test weight, shelling percent, and kernel yield per plant showed high heritability indicating that the variation was caused by additive gene action. The correlation estimates provide a better understanding of yield components and studies on genotypic and phenotypic correlation coefficients of different traits help the plant breeder during selection.

GENETIC VARIANCE IN HEPARAN SULFATION IS ASSOCIATED WITH SALT-SENSITIVITY: A GENE-ENVIRONMENT ANALYSIS

Objective: The high heritability of salt sensitivity suggests an essential role for genetic variants in the relationship between sodium intake and blood pressure (BP). Candidate gene studies have mainly focused on renal and vascular pathways, but the role of glycosaminoglycan (GAG) genes, which are crucial for salinity tolerance, remains to be elucidated. Design and method: Interactions between 54,126 variants in 130 GAG genes and daily sodium excretion on BP were explored in 20,420 EPIC-Norfolk subjects. UK Biobank (n=414,132) and the multi-ethnic HELIUS study (n=2,239) were used for validation. In HELIUS sodium intake was estimated with Food Frequency Questionnaires (FFQ). Urinary GAG composition in 57 Dutch origin HELIUS participants stratified by genotype were analyzed to assess the association between SNP and GAG difference. Also, urinary GAG composition in 12 healthy volunteers after a sodium intervention (7-day low (50 mmol Na+/day) and 7-day high (200 mmol Na+/day) diet) were studied to assess if differences in genotype are associated with different GAG expression. Results: The intron variant rs2892799, mapped to NDST3, showed the strongest interaction with sodium on mean arterial pressure (MAP) (FDR 0.03), and the intron variant rs9654628 mapped to HS3ST5 with sodium on systolic BP (FDR 0.03). These interactions were multi-ethnically validated (Fig 1A, B). When stratified for rs2892799 genotype, T-allele carriers had a significantly higher urinary expression of N-sulfated heparan sulfate epitope D0S0 (Fig1C). Conversely, upon dietary salt loading, urinary D0S0 expression differed substantially between salt-sensitive and salt-resistant individuals (Fig1D). Sodium-induced effects on this epitope were opposite in salt-sensitive in salt-resistant individuals. Conclusions: Genetic variants associated with NDST3 and HS3ST5 interact with relation between sodium consumption and BP. rs2892799 (NDST3) genotype results in a different expression of the N-sulfated D0S0 epitope. In turn, D0S0 expression is associated with salt-mediated BP increase, indicating that genetic GAG variation and metabolic GAG adaptation to a high salt environment might be important for human BP regulation.

A Comprehensive study of wheat genotypes for combining ability and heritability in drought tolerance

A major challenge in wheat cultivation is the negative impact of water scarcity on growth and yield. Therefore, it is crucial to develop wheat varieties with both high productivity and resilience to drought stress to support food production and improve global food security. The study aims to identify general and specific combining abilities and to understand the genetic mechanisms responsible for key traits by employing half-diallel analysis. In the current study, a half-diallel set comprising 10 x 10 wheat genotypes was subjected to crosses in all feasible combinations, excluding reciprocals, under drought stress conditions. Significant mean squares were observed for both General Combining Ability (GCA) and Specific Combining Ability (SCA) components among the 10 parents and 45 F1 progenies across eleven traits. Assessment of variance components (s2g and s2s), narrow-sense heritability (Hn), broad-sense heritability (Hb) and the GCA/SCA ratio allowed for the determination of the relative contributions of additive and non-additive genetic components. High narrow-sense heritability was noted for traits such as days to 75 % flowering, spike length and biological yield, indicating their predominantly additive genetic control. Conversely, the remaining eight traits exhibited low narrow-sense heritability, suggesting their inheritance is primarily governed by non-additive genetic factors, thus indicating the potential benefits of heterosis breeding. Based on GCA effects, P5 demonstrated superior general combining ability across traits, except for biological yield. P1, P3, P8 and P9 exhibited better combining ability for grain yield per plant. Specific cross combinations including P7×P10, P3×P4 and P5×P6 displayed notable specific combining ability and could be leveraged to develop superior pure lines in subsequent breeding endeavors.

Association of whole-person eigen-polygenic risk scores with Alzheimer's disease.

Late-Onset Alzheimer's Disease (LOAD) is a heterogeneous neurodegenerative disorder with complex etiology and high heritability. Its multifactorial risk profile and large portions of unexplained heritability suggest the involvement of yet unidentified genetic risk factors. Here we describe the "whole person" genetic risk landscape of polygenic risk scores for 2218 traits in 2044 elderly individuals and test if novel eigen-PRSs derived from clustered subnetworks of single-trait PRSs can improve the prediction of LOAD diagnosis, rates of cognitive decline, and canonical LOAD neuropathology. Network analyses revealed distinct clusters of PRSs with clinical and biological interpretability. Novel eigen-PRSs (ePRS) from these clusters significantly improved LOAD-related phenotypes prediction over current state-of-the-art LOAD PRS models. Notably, an ePRS representing clusters of traits related to cholesterol levels was able to improve variance explained in a model of the brain-wide beta-amyloid burden by 1.7% (likelihood ratio test P = 9.02 × 10-7). All associations of ePRS with LOAD phenotypes were eliminated by the removal of APOE-proximal loci. However, our association analysis identified modules characterized by PRSs of high cholesterol and LOAD. We believe this is due to the influence of the APOE region from both PRSs. We found significantly higher mean SNP effects for LOAD in the intersecting APOE region SNPs. Combining genetic risk factors for vascular traits and dementia could improve current single-trait PRS models of LOAD, enhancing the use of PRS in risk stratification. Our results are catalogued for the scientific community, to aid in generating new hypotheses based on our maps of clustered PRSs and associations with LOAD-related phenotypes.

Genetic Variability and Character Association Studies in Diverse Rice (Oryza sativa L.) Genotypes for Agro-Morphological Traits in Terai Region of West Bengal

Aims: The study aims to analyze the genetic variability in diverse rice genotypes and establish correlations with grain yield and its attributes. By identifying and quantifying the genetic elements influencing grain yield and associated traits, the research intends to offer insights for developing high-yielding and resilient rice varieties, ultimately enhancing food security and agricultural sustainability. Study Design: The experiment was set up in a randomized complete block design (RCBD) with two replications, using a spacing of 20 cm × 15 cm. Place and Duration of Study: The experiment was conducted at the Instructional Farm of Uttar Banga Krishi Viswavidyalaya, Pundibari, Cooch Behar, West Bengal during the Kharif season (the period from June to October) of 2019 and 2020. The duration of the study encompassed the entire Kharif seasons of both years. Methodology: The study evaluated forty-two diverse rice genotypes based on nine agro-morphological traits. The methodology encompassed the utilization of ANOVA to evaluate significant differences in trait means and discern genetic variability among rice genotypes. Central tendency and variability were assessed through the calculation of mean, range, and standard deviation to gain insights into genetic variation. Furthermore, variation among traits was quantified using phenotypic and genotypic coefficient of variation to aid in understanding genetic variability. Heritability in broad sense was estimated to ascertain the genetic contribution to the observed variation, while the identification of traits with potential for improvement was achieved through the analysis of genetic advance as percent of mean. Furthermore, correlation and path coefficient analyses were conducted to comprehend the connections between the agro-morphological traits and grain yield, offering insights into the genetic relationships among the traits and their direct and indirect impacts on grain yield patterns. Results: The analysis of variance results confirmed the presence of significant differences among the evaluated genotypes. The phenotypic coefficient of variation displayed elevated values, closely associated with the genotypic coefficient of variation for all traits. Both phenotypic and genotypic coefficient of variation values were observed to be low to moderate for all the nine traits. Furthermore, specific traits such as grain breadth, panicles plant-1, and grain L/B ratio exhibited high heritability and high genetic advance percentage of mean, indicating their potential for selection and improvement in breeding programs. Additionally, the correlation study at the genotypic level revealed positive and significant correlations between grain yield plant-1, test weight, and spikelet fertility. Moreover, the path coefficient analysis showed that grain length had the maximum positive direct effect on grain yield plant-1. Conclusion: In conclusion, the analysis revealed significant genotype variations across multiple traits, indicating potential for targeted breeding improvements. Traits like grain breadth, panicles plant-1, and grain L/B ratio showed promising heritability and genetic advancement, emphasizing their value for selection in breeding programs. Correlation and path coefficient analyses highlighted interrelationships and direct effects on yield, underlining the importance of genetic factors in trait expression.

Genetic diversity and stability analysis based on agro-morphological traits among rice genotypes developed through marker-assisted backcrossing

Background: The genetic diversity and stability analysis based on agro-morphological traits among rice genotypes developed through SSR marker-assisted backcrossing was evaluated at college of agricultural science (CAS), Ebonyi State niversity, Abakaliki, Nigeria. Methods: In this study, 9 rice accessions sourced from the Iinstitute of tropical agriculture and food security (ITAFoS), universiti Putra, Malaysia and Ebonyi, Nigeria; were evaluated for yield stability performance. The experiments were laid out in randomized complete block design (RCBD) with three replications each for two seasons. Results: Result of the evaluated rice accessions showed highly marked morphological variability based on the mean performance and were grouped into three main clusters. Cluster I had CP, cluster II contained Line4, Line5, Line6, and Line8, and cluster III had Line1, Line7, Line12, and Putra-1. The first, 3 principal components were identified and retained for having the Eigen-value >1. The first PC had an eigenvalue of (6.30) with 52.5% proportion of which plant height accounted most for this variation with (0.359) whereas panicle length contributed the least (-0.13). For stability analysis, CP had highest values for most of the parameters. High heritability value was recorded for all nine traits which range between 71.04% and 95.06%. The highest heritability value (95.06%) was found in Days 50% heading while grain width had the lowest (71.04%). Conclusions: It could be concluded that CP, Putral-1, and line7 were the most stable in terms of yield across the two seasons of this study; hence, recommended for parental materials for hybridization.

Genome-wide association analysis of eggshell color of an F2 generation population reveals candidate genes in chickens

Eggshell color is an important visual characteristic that affects consumer preferences for eggs. Eggshell color, which has moderate to high heritability, can be effectively enhanced through molecular marker selection. Various studies have been conducted on eggshell color at specific time points. However, few longitudinal data are available on eggshell color. Therefore, the objective of this study was to investigate eggshell color using the Commission International de L'Eclairage L*a*b* system with multiple measurements at different ages (age at the first egg and at 32, 36, 40, 44, 48, 52, 56, 60, 66, and 72 weeks) within the same individuals from an F2 resource population produced by crossing White Leghorn and Dongxiang Blue chicken. Using an Affymetrix 600 single nucleotide polymorphism (SNP) array, we estimated the genetic parameters of the eggshell color trait, performed genome-wide association studies (GWASs), and screened for the potential candidate genes. The results showed that pink-shelled eggs displayed a significant negative correlation between L* values and both a* and b* values. Genetic heritability based on SNPs showed that the heritability of L*, a*, and b* values ranged from 0.32 to 0.82 for pink-shelled eggs, indicating a moderate to high level of genetic control. The genetic correlations at each time point were mostly above 0.5. The major-effect regions affecting the pink eggshell color were identified in the 10.3–13.0 Mb interval on Gallus gallus chromosome 20, and candidate genes were selected, including SLC35C2, PCIF1, and SLC12A5. Minor effect polygenic regions were identified on chromosomes 1, 6, 9, 12, and 15, revealing 11 candidate genes, including MTMR3 and SLC35E4. Members of the solute carrier family play an important role in influencing eggshell color. Overall, our findings provide valuable insights into the phenotypic and genetic aspects underlying the variation in eggshell color. Using GWAS analysis, we identified multiple quantitative trait loci (QTLs) for pink eggshell color, including a major QTL on chromosome 20. Genetic variants associated with eggshell color may be used in genomic breeding programs.